WARNING : tensorflow:Model was constructed with shape

I created a model. but when I want the model to do the estimation, I get an error.

inputs = tf.keras.Input(shape=(512, 512,1))

conv2d_layer = tf.keras.layers.Conv2D(32, (2,2), padding='Same')(inputs)
conv2d_layer = tf.keras.layers.Conv2D(32, (2,2), activation='relu', padding='Same')(conv2d_layer)

bn_layer = tf.keras.layers.BatchNormalization()(conv2d_layer)
mp_layer = tf.keras.layers.MaxPooling2D(pool_size=(2,2))(bn_layer)
drop = tf.keras.layers.Dropout(0.25)(mp_layer)

conv2d_layer = tf.keras.layers.Conv2D(64, (2,2), activation='relu', padding='Same')(drop)
conv2d_layer = tf.keras.layers.Conv2D(64, (2,2), activation='relu', padding='Same')(conv2d_layer)

bn_layer = tf.keras.layers.BatchNormalization()(conv2d_layer)
mp_layer = tf.keras.layers.MaxPooling2D(pool_size=(2,2), strides=(2,2))(bn_layer)
drop = tf.keras.layers.Dropout(0.25)(mp_layer)

flatten_layer = tf.keras.layers.Flatten()(drop)

dense_layer = tf.keras.layers.Dense(512, activation='relu')(flatten_layer)
drop = tf.keras.layers.Dropout(0.5)(dense_layer)
outputs = tf.keras.layers.Dense(2, activation='softmax')(drop)

model = tf.keras.Model(inputs=inputs, outputs=outputs, name='tumor_model')
model.summary()

Train Images Shape (342, 512, 512, 1)
Train Labels Shape (342, 2)
Test Images Shape (38, 512, 512, 1)
Test Labels Shape (38, 2)

Problem Here:

pred = model.predict(test_images[12])

WARNING:tensorflow:Model was constructed with shape (None, 512, 512, 1) for input KerasTensor(type_spec=TensorSpec(shape=(None, 512, 512, 1), dtype=tf.float32, name=’input_1′), name=’input_1′, description="created by layer ‘input_1’"), but it was called on an input with incompatible shape (32, 512, 1, 1).